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Aligning and Merging Biomedical Ontologies
Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems. Linköping University, The Institute of Technology.
2006 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Due to the explosion of the amount of biomedical data, knowledge and tools that are often publicly available over the Web, a number of difficulties are experienced by biomedical researchers. For instance, it is difficult to find, retrieve and integrate information that is relevant to their research tasks. Ontologies and the vision of a Semantic Web for life sciences alleviate these difficulties. In recent years many biomedical ontologies have been developed and many of these ontologies contain overlapping information. To be able to use multiple ontologies they have to be aligned or merged. A number of systems have been developed for aligning and merging ontologies and various alignment strategies are used in these systems. However, there are no general methods to support building such tools, and there exist very few evaluations of these strategies. In this thesis we give an overview of the existing systems. We propose a general framework for aligning and merging ontologies. Most existing systems can be seen as instantiations of this framework. Further, we develop SAMBO (System for Aligning and Merging Biomedical Ontologies) according to this framework. We implement different alignment strategies and their combinations, and evaluate them in terms of quality and processing time within SAMBO. We also compare SAMBO with two other systems. The work in this thesis is a first step towards a general framework that can be used for comparative evaluations of alignment strategies and their combinations.

Place, publisher, year, edition, pages
Institutionen för datavetenskap , 2006. , 14 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1225
Series
Keyword [en]
Ontologies, Ontology engineering, Biomedical ontologies, Ontology alignment, Ontology alignment, Ontology merging
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:liu:diva-6201ISBN: 91-85497-01-0 (print)OAI: oai:DiVA.org:liu-6201DiVA: diva2:21691
Presentation
2006-01-23, Visionen, Hus B, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Note
Report code: LiU-Tek-Lic-2006:6.Available from: 2006-04-03 Created: 2006-04-03 Last updated: 2015-02-18
List of papers
1. SAMBO – A System for Aligning and Merging Biomedical Ontologies
Open this publication in new window or tab >>SAMBO – A System for Aligning and Merging Biomedical Ontologies
2006 (English)In: Journal of Web Semantics, ISSN 1570-8268, E-ISSN 1873-7749, Vol. 4, no 3, 196-206 p.Article in journal (Refereed) Published
Abstract [en]

Due to the recent explosion of the amount of on-line accessible biomedical data and tools, finding and retrieving the relevant information is not an easy task. The vision of a Semantic Web for life sciences alleviates these difficulties. A key technology for the Semantic Web is ontologies. In recent years many biomedical ontologies have been developed and many of these ontologies contain overlapping information. To be able to use multiple ontologies they have to be aligned or merged. In this paper we propose a framework for aligning and merging ontologies. Further, we developed a system for aligning and merging biomedical ontologies (SAMBO) based on this framework. The framework is also a first step towards a general framework that can be used for comparative evaluations of alignment strategies and their combinations. In this paper we evaluated different strategies and their combinations in terms of quality and processing time and compared SAMBO with two other systems.

Place, publisher, year, edition, pages
Elsevier, 2006
Keyword
Ontologies; Alignment; Merging; Biomedical informatics
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-14575 (URN)10.1016/j.websem.2006.05.003 (DOI)000247054000005 ()
Available from: 2007-07-03 Created: 2007-07-03 Last updated: 2016-12-06Bibliographically approved
2. Alignment of Biomedical Ontologies using Life Science Literature
Open this publication in new window or tab >>Alignment of Biomedical Ontologies using Life Science Literature
Show others...
2006 (English)In: Proceedings of the International Workshop on Knowledge Discovery in Life Science Literature / [ed] Eric G. Bremer, Springer Berlin/Heidelberg, 2006, 1-17 p.Chapter in book (Refereed)
Abstract [en]

This book constitutes the refereed proceedings of the International Workshop on Knowledge Discovery in Life Science Literature, KDLL 2006, held in Singapore in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006).

The 12 revised full papers presented together with two invited talks were carefully reviewed and selected for inclusion in the book. The papers cover all topics of knowledge discovery in life science data such as text mining, identification and retrieval of documents, passage retrieval, co-reference resolution, extraction of life science entities or relationships from large collections, automated characterization of biological, biomedical and biotechnological entities and processes, extraction and characterization of more complex patterns and interaction networks, automated generation of text summaries, automated construction, expansion and curation of ontologies for different domains, and construction of controlled vocabularies.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2006
Series
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 3886
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-14035 (URN)10.1007/11683568_1 (DOI)000237198800001 ()978-3-540-32809-4 (ISBN)3-540-32809-2 (ISBN)
Available from: 2006-09-28 Created: 2006-09-28 Last updated: 2016-12-06Bibliographically approved

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Tan, He

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Citation style
  • apa
  • harvard1
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  • Other style
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  • de-DE
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  • Other locale
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Output format
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